Modeling Task Scheduling Decisions of Emergency Department Physicians.

Objective: This study evaluated task-scheduling decisions in the context of emergency departments by comparing patterns of emergency physicians' task-scheduling models across levels of experience.

Background: Task attributes (priority, difficulty, salience, and engagement) influence task-scheduling decisions. However, it is unclear how attributes interact to affect decisions, especially in complex contexts. An existing model of task scheduling, strategic task overload management-no priority (STOM-NP), found that an equal weighting of attributes can predict task-scheduling behavior. Alternatively, mathematical modeling estimated that priority alone could make similar predictions as STOM-NP in a parsimonious manner. Experience level may also influence scheduling decisions.

Method: An experimental design methodology shortened a judgment analysis approach to compare a priori task-scheduling decision strategies. Emergency physicians with two levels of experience rank-ordered 10 sets of 3 tasks varying on 4 task attributes in this complex environment.

Results: Bayesian statistics were used to identify best-fit decision strategies. STOM-NP and priority-only provided the best model fits. STOM-NP fit the lower-experienced physicians best, whereas priority-only-using only one cue-fit the higher-experienced physicians best.

Conclusion: Models of decision strategies for task-scheduling decisions were extended to complex environments. Experts' level of experience influenced task-scheduling decisions, where the scheduling decisions of more-experienced experts was consistent with a more frugal decision process. Findings have implications for training and evaluation.

Application: We assessed models of cues that influence task-scheduling decisions, including a parsimonious model for task priority only. We provided a sample approach for shortening methods for understanding decisions.